Engineering Manager — Enterprise Data Warehouse & Analytics

Machinify; United States; Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Remote work in the US

Medical/Dental/Vision

Equity

401(k) employer match

Unlimited PTO

Job summary

Machinify is seeking an Engineering Manager to lead a data warehouse and analytics team focused on a Databricks lakehouse. You will own the dimensional model, design ETL/ELT pipelines, and govern metrics used across Power BI dashboards and LLM queries.

You will collaborate with Product and Operations to shape requirements, deliver reliable metrics, and modernize orchestration. A hands-on manager with strong SQL/dbt and cloud data engineering experience is essential.

Qualifications

• Over 10 years in data warehousing, data engineering, or analytics engineering.
• At least 3+ years as a hands‑on engineering manager.
• Expertise in dimensional modeling: grain, conformed dimensions, SCDs, bus matrix.
• Expert SQL and dbt: complex SQL, tests, macros, CI.
• Databricks in production: Spark SQL, Delta Lake, Unity Catalog."
• Knowledge of BI semantic layers and governance for metrics (Power BI, dbt Semantic Layer/MetricFlow).
• Experience with ETL/ELT orchestration (Airflow) and Python for pipelines.
• Data quality, tests, reconciliation, observability, and CI/CD for data.

Responsibilities

• Own the data model: design and evolve the conformed dimensional model and standards; review new models for grain and conformance.
• Build and run pipelines: design ETL/ELT from sources through bronze → silver → gold on Databricks with incremental loads and data contracts.
• Own the semantic layer: build governed metrics and semantic models for dashboards and LLM queries.
• Deliver reliable operational metrics: turn KPI definitions into certified models and metrics; reconcile to source and deliver via dashboards.
• Assure the numbers: reconciliation, data tests, freshness, anomaly monitoring, SLOs, CI/CD for data.
• Modernize orchestration: move dbt orchestration from dbt Cloud to Airflow with no data freshness gaps.
• Partner with Product: translate requirements into architectural plans, sequencing, estimates, and trade-offs.
• Lead the team: coach and hire analytics engineers/BI analysts; enforce code review, testing, docs, and AI-assisted development.

Skills

Leadership

Cross-functional collaboration

Mentoring

Communication

Tools

Databricks

dbt

Airflow

Power BI

SQL

Python

Delta Lake

Unity Catalog

Snowflake/BigQuery

Job description

Machinify is seeking an Engineering Manager to lead a data warehouse and analytics team focused on a Databricks lakehouse. You will own the dimensional model, design ETL/ELT pipelines, and govern metrics used across Power BI dashboards and LLM queries.

You will collaborate with Product and Operations to shape requirements, deliver reliable metrics, and modernize orchestration. A hands-on manager with strong SQL/dbt and cloud data engineering experience is essential.